Econometrics 2013, 1(2), 141-156; doi:10.3390/econometrics1020141
Article

Generalized Empirical Likelihood-Based Focused Information Criterion and Model Averaging

Graduate School of Economics, Kyoto University, Yoshida-Hommachi, Sakyo-ku, Kyoto, 6068501,Japan
Received: 13 May 2013; in revised form: 26 June 2013 / Accepted: 27 June 2013 / Published: 3 July 2013
(This article belongs to the Special Issue Econometric Model Selection)
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Abstract: This paper develops model selection and averaging methods for moment restriction models. We first propose a focused information criterion based on the generalized empirical likelihood estimator. We address the issue of selecting an optimal model, rather than a correct model, for estimating a specific parameter of interest. Then, this study investigates a generalized empirical likelihood-based model averaging estimator that minimizes the asymptotic mean squared error. A simulation study suggests that our averaging estimator can be a useful alternative to existing post-selection estimators.
Keywords: model selection; model averaging; focused information criterion; generalized empirical likelihood

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MDPI and ACS Style

Sueishi, N. Generalized Empirical Likelihood-Based Focused Information Criterion and Model Averaging. Econometrics 2013, 1, 141-156.

AMA Style

Sueishi N. Generalized Empirical Likelihood-Based Focused Information Criterion and Model Averaging. Econometrics. 2013; 1(2):141-156.

Chicago/Turabian Style

Sueishi, Naoya. 2013. "Generalized Empirical Likelihood-Based Focused Information Criterion and Model Averaging." Econometrics 1, no. 2: 141-156.

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